Evidence map›Paper›PMID 36986737›Full record

ArticlePharmaceutics2023

Electrochemical Nano-Imprinting of Trimetallic Dendritic Surface for Ultrasensitive Detection of Cephalexin in Pharmaceutical Formulations.

Rohini Kumari, Pranjal Chandra

Open access · goldAbstract read
In one paragraph

Article in Pharmaceutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
8.0field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 33 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Rohini KumariLaboratory of Bio-Physio Sensors and Nanobioengineering, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India.ORCID 0000-0001-7411-8093
Pranjal ChandraLaboratory of Bio-Physio Sensors and Nanobioengineering, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India.ORCID 0000-0003-3428-3195
Indian Institute of Technology BHU · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cephalexin (CFX), a first-generation cephalosporin, is used to treat various infectious diseases. Although antibiotics have achieved considerable progress in the eradication of infectious diseases, their incorrect and excessive usage has contributed to various side effects, such as mouth soreness, pregnancy-related pruritus, and gastrointestinal symptoms, including nausea, epigastric discomfort, vomiting, diarrhoea, and haematuria. In addition to this, it also causes antibiotic resistance, one of the most pressing problems in the medical field. The World Health Organization (WHO) claims that cephalosporins are currently the most commonly used drugs for which bacteria have developed resistance. Hence, it is crucial to detect CFX in complex biological matrices in a highly selective and sensitive way. In view of this, a unique trimetallic dendritic nanostructure comprised of cobalt, copper, and gold was electrochemically imprinted on an electrode surface by optimising the electrodeposition variables. The dendritic sensing probe was thoroughly characterised using X-ray photoelectron spectroscopy, scanning electron microscopy, chronoamperometry, electrochemical impedance spectroscopy, and linear sweep voltammetry. The probe displayed superior analytical performance, with a linear dynamic range between 0.05 nM and 10

Indexed as

cephalexinelectrochemical nano-imprintingsurface engineeringtrimetallic AuCoCu NDs

Identifiers

PMID36986737
PMCPMC10058315
OpenAlexW4323569043

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.